Grokking the Machine Learning Interview

The course will help you ace the machine learning interview question patterns, ensuring a smooth and enjoyable interview experience.

Intermediate

49 Lessons

15h

Certificate of Completion

The course will help you ace the machine learning interview question patterns, ensuring a smooth and enjoyable interview experience.

AI-POWERED

Mock Interview

Explanations

AI-POWERED

Mock Interview

Explanations

Course Overview

System design is an important component of any ML interview. Being able to efficiently solve open-ended machine learning problems is a key skill that can set you apart from other engineers and increase the level of seniority at which you’re hired. This course helps you build that skill, and goes over some of the most popularly asked interview problems at big tech companies. You’ll walk step-by-step through solving these problems, focusing in particular on how to design machine learning systems rather than ...Show More

TAKEAWAY SKILLS

Machine Learning

Prepare For Interview

Course Content

Introduction

In this chapter, you will learn how this course prepares you for ML system design interviews, covering ML rise, interview expectations, and setup steps.

How Does This Course Help in ML Interviews?

Setting up a Machine Learning System

Practical ML Techniques/Concepts

In this chapter, you will explore ML techniques: performance and capacity, data collection, online experiments, embeddings, transfer learning, and debugging.

Performance and Capacity Considerations Training Data Collection Strategies Online Experimentation Embeddings Transfer Learning Model Debugging and Testing

Search Ranking

In this chapter, you will discover how to design a search ranking system, covering problem definition, metrics, architecture, document selection, and more.

Problem Statement Metrics Architectural Components Document Selection Feature Engineering Training Data Generation Ranking Filtering Results

Feed Based System

This chapter explores designing a Twitter feed system, covering problem statements, metrics, tweet selection, feature engineering, ranking, and more.

Problem Statement Metrics Architectural Components Tweet Selection Feature Engineering Training Data Generation Ranking Diversity Online Experimentation

Recommendation System

In this chapter, you will explore building a recommendation system by defining problems, metrics, architecture, feature engineering, and ranking methods.

Problem Statement Metrics Architectural Components Feature Engineering Candidate Generation Training Data Generation Ranking

Self-Driving Car: Image Segmentation

5 Lessons

In this chapter, you’ll explore image segmentation for self-driving cars, covering problem statements, metrics, architecture, data generation, and modeling.

Entity Linking System

5 Lessons

In this chapter, you’ll learn to build an entity linking system, evaluate it with metrics, and explore components, training data, and models like ELMo and BERT.

Ad Prediction System

7 Lessons

This chapter focuses on building ad prediction systems, covering metrics, architecture, feature engineering, data generation, ad selection, and prediction.

Course Author

Trusted by 1.4 million developers working at companies

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

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Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

AI-Powered Mock Interviews

Put your skills to the test in a simulated interview setting. Receive personalized feedback based on your performance. Available in Premium & Premium Plus plans.

Adaptive Learning

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Explain with AI

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AI Code Mentor

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